Regional Ocean Forecasting System

The ROFS Division addresses the following streams of activities:

  1. Managing and Enhancing the Copernicus Mediterranean and Black Sea Systems:
    The division leads efforts in coordinating, optimizing, and developing reanalysis, analysis, and forecast systems for the Mediterranean and Black Sea regions within the Copernicus Marine Service.
  2. Development of Regional Ocean Modeling and Data Assimilation:
    The division develops and implements state-of-the-art regional ocean models and data assimilation systems specifically targeting the Mediterranean and Black Sea regions and it is involved in the innovation, design and development of regional forecasting systems, including coupled and ensemble forecasting systems.
  3. Optimizing Operational Chains:
    The division is committed to the continuous maintenance, optimization, and enhancement of operational chains for forecasting systems in the Mediterranean (MedFS), Black Sea (BSFS), and Global Ocean (GOFS16) domains.
  4. Streamlining Data Management:
    The division implements data management, archiving, and delivery tools to facilitate the access of critical data for forecasting activities.

ROFS Projects

  • FOCCUS - Forecasting and observing the open-to-coastal ocean for Copernicus users

    FOCCUS enhances CMEMS (Copernicus Marine Environment Monitoring Service), for effective uptakes from…


  • ECMWF DE_350: Visualisation & Immersive Technologies

    The contract covers the Contractor’s contribution to the design, development, manufacturing, installation,…


  • IRIDE (Precursor phase)

    The IRIDE program is an innovative project undertaken by the Italian government,…

  • Division Director

    Emanuela Clementi

    Division Manager

    Contacts

    Via Marco Biagi, 5 — 73100 Lecce, Italy
    [email protected]
    0832 1902411

    ROFS Publications

    Machine learning methods to predict sea surface temperature and marine heatwave occurrence: a case study of the Mediterranean Sea

    Bonino G., Galimberti G.; Masina S., McAdam R., Clementi E.
    2024, Ocean Science, Volume 20, Issue 2, Pages 417 - 432, doi: 10.5194/os-20-417-2024

    Published articles


    A Data Filling Methodology for Time Series Based on CNN and (Bi)LSTM Neural Networks

    Tzoumpas K.; Estrada A.; Miraglio P., Zambelli P.
    2024, IEEE Access, Volume 12, Pages 31443 - 31460, doi: 10.1109/ACCESS.2024.3369891

    Published articles


    Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea

    Maglietta R.; Saccotelli L., Fanizza C.; Telesca V.; Dimauro G.; Causio S., Lecci R., Federico I., Coppini G., Cipriano G.; Carlucci R.
    2023, Scientific Reports, Volume 13, Issue 1 - Article number 2600, doi: 10.1038/s41598-023-29681-y

    Published articles

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